Senior Applied Scientist- Microsoft Store

6 months ago

Suzhou, China Microsoft Full time

Overview

Microsoft Store is a digital distribution platform developed by Microsoft on Windows Desktop. It serves as a centralized hub for users to discover, download, and manage various types of applications, software, games, and other digital content. The vision of the Microsoft Store aligns with Microsoft's broader mission to empower individuals and organizations to achieve more through technology. The store aims to provide users with a convenient and secure platform to access a diverse range of high-quality digital content that enhances productivity, creativity, and entertainment on Windows devices.

We are seeking a motivated and strategic-thinking Senior Applied Scientist to join the Microsoft Store China team in Suzhou or Beijing. In this role, you will have the opportunity to impact millions of store users, enabling them to enjoy a diverse array of benefits and features that elevate their digital experience.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Qualifications

Required Qualifications

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)OR equivalent experience 5+ years of experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets. 3+ years of industry experience with implementing statistical models, machine/deep learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment. 

Preferred Qualifications

Master's Degree in Statistics, Econometrics, Computer Science, ElectricalOR Computer Engineering,OR related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)OR Doctorate in Statistics, Econometrics, Computer Science, ElectricalOR Computer Engineering,OR related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)OR equivalent experience Experience with experiments, machine learning, anomaly detection, predictive analysis, exploratory data analysis, and/or other areas of data science on a large-scale product. Experience with languages like C#/Java is a plus. Engineering experience using large data systems on SQL, Hadoop, Hive queries, etc.is nice to have. 

Responsibilities

Work with partners, product managers and developers to develop & review designs and business requirement. Apply statistical concepts and techniques to analyze product quality, experiments and user behavior. Design & develop data transformation processes for petabytes of raw data, perform feature engineering for machine learning. Develop predictive and prescriptive models using advanced research techniques. Communicate complex quantitative analysis in a clear, precise, and actionable manner to non-technical audiences. Collaborate with partners and drive analytic projects end to end. Adhere to principled data collection practices and policies Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect

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